Triple

T17772827
Position Surface form Disambiguated ID Type / Status
Subject Obolonsko–Teremkivska line E443683 entity
Predicate hasStation P35 FINISHED
Object Demiivska
Demiivska is a metro station on the Kyiv Metro system in Ukraine, serving the Demiivka neighborhood in the southern part of the city.
 E1287526 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Demiivska | Statement: [Obolonsko–Teremkivska line, hasStation, Demiivska]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Demiivska
Context triple: [Obolonsko–Teremkivska line, hasStation, Demiivska]
  • A. Dolianova
    Dolianova is a small town in southern Sardinia, Italy, known for its wine production and historic Romanesque cathedral.
  • B. Baklanova
    Baklanova is a Russian feminine surname, typically derived from the masculine form Baklanov.
  • C. Malisheva
    Malisheva is a town and municipality in central Kosovo known for its location in the historical Dukagjin region and its role as a local administrative and economic center.
  • D. Vasishka
    Vasishka was a Kushan emperor who ruled parts of northern India and Central Asia in the early 3rd century CE, known primarily from his inscriptions and coinage.
  • E. Karsavina
    Karsavina is the surname of Tamara Karsavina, a renowned Russian prima ballerina of the early 20th century.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Demiivska
Triple: [Obolonsko–Teremkivska line, hasStation, Demiivska]
Generated description
Demiivska is a metro station on the Kyiv Metro system in Ukraine, serving the Demiivka neighborhood in the southern part of the city.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Demiivska
Target entity description: Demiivska is a metro station on the Kyiv Metro system in Ukraine, serving the Demiivka neighborhood in the southern part of the city.
  • A. Dolianova
    Dolianova is a small town in southern Sardinia, Italy, known for its wine production and historic Romanesque cathedral.
  • B. Baklanova
    Baklanova is a Russian feminine surname, typically derived from the masculine form Baklanov.
  • C. Malisheva
    Malisheva is a town and municipality in central Kosovo known for its location in the historical Dukagjin region and its role as a local administrative and economic center.
  • D. Vasishka
    Vasishka was a Kushan emperor who ruled parts of northern India and Central Asia in the early 3rd century CE, known primarily from his inscriptions and coinage.
  • E. Karsavina
    Karsavina is the surname of Tamara Karsavina, a renowned Russian prima ballerina of the early 20th century.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d8b9ef17708190bdf7e2adbf14ddc2 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4871a2130819081743ae89dddc64b completed April 19, 2026, 7:41 a.m.
NED1 Entity disambiguation (via context triple) batch_6a02efc6004c819095f9b6284b015b8d completed May 12, 2026, 9:15 a.m.
NEDg Description generation batch_6a02f113a41c8190b17611eaa50516ca completed May 12, 2026, 9:21 a.m.
NED2 Entity disambiguation (via description) batch_6a02f1e980f4819087eb191e13396581 completed May 12, 2026, 9:24 a.m.
Created at: April 10, 2026, 10:12 a.m.